Oaks and Landforms

Raster map of suitable landforms

The map below depicts areas where suitable landforms coincide with areas mapped as having oak-containing ecosystems (see methods below for lists of oak-containing ecosystems and selected landforms). The landforms data comes from the Center for Resilient Science. The basic idea is that the warmer and drier landforms might give oaks a competitive advantage over more mesophytic tree species.

When looking at the data across the region, patterns can be hard to detect. The zoomed in map below of Juneau county, WI illustrates more heterogeneity.

Percentage of oak-containing ecosystems on suitable landforms by HUC 12 watershed

The map below depicts the percentage of each watershed that was mapped as having oak-containing EVTs as of 2023 that occur on suitable landforms.

Brief methods

General data processing

For the maps we:

1. Use LANDFIRE’s Existing Vegetation Types data to map oak dominated ecosystems. This data was clipped to the dissolved HUC 12 watersheds boundary shapefile. See R code below for lists of ecosystems and landforms.
2. Combined these oak areas with the Landforms dataset developed by The Nature Conservancy’s Center for Resilient Conservation Science. This dataset ‘subdivides landscapes into local topographic units with unique moisture and temperature profiles’ (from the dataset’s webpage linked above).
3. Exported the attribute table as “evt_landforms_combine.csv”. Ran the code below to append a column that essentially says “yes or no, oak-containing ecosystems occuring on suitable landforms”.
4. This new column was joined back to the combined evt_landform_combine raster.

The top map on this page was made with the raw raster data.

For the HUC 12 map I used the Zonal Statistics as Table tool to get the number of pixels labeled as “1” (i.e., oak containing ecosystem occuring on suitable landforms) per watershed , statistics type = SUM. I then multiplied the SUM by 0.2224 to get acres.

Code for identifying oak-containing ecosystems and suitable landforms

The code below was run in R to add a new column named “in_y_n” to the evt_landforms_combine.csv data for joining to combined evt_landforms raster.

target_evt_names <- c(
  "North-Central Interior Dry-Mesic Oak Forest and Woodland",
  "North-Central Interior Dry Oak Forest and Woodland",
  "Laurentian-Acadian Northern Pine-(Oak) Forest",
  "Laurentian-Acadian Northern Oak Forest",
  "North-Central Oak Barrens Woodland",
  "Laurentian Pine-Oak Barrens",
  "Laurentian Oak Barrens",
  "North-Central Oak Barrens Herbaceous",
  "North-Central Interior Oak Savanna",
  "Southern Interior Low Plateau Dry-Mesic Oak Forest",
  "Northern & Central Native Ruderal Forest",
  "Northern & Central Ruderal Meadow",
  "Northern & Central Ruderal Shrubland"
)

# Updated list of acceptable Landforms
target_landforms <- c(
  "Steep slope: SW warm",
  "Cliff: SW warm",
  "Flat summit/ridge",
  "Slope crest",
  "Upper flat",
  "Gentle slope",
  "Sideslope SW warm",
  "Lower Slope SW warm",
  "Dry flat",
  "Cove: SW warm"
)

# Add the new column based on both conditions
evt_landforms <- evt_landforms %>%
  mutate(in_y_n = if_else(EVT_NAME %in% target_evt_names & Landforms %in% target_landforms, 1, 0))

write_csv(evt_landforms, file = "outputs/evt_landforms_to_join.csv")